---
title: "Advanced Dashboarding"
output: 
  flexdashboard::flex_dashboard:
    orientation: row    # or column
    vertical_layout: fill
    social: ["menu"]
    source_code: embed
    theme:
      version: 4
      bootswatch: sandstone # a preset CSS style, bootswatch.com
---

```{r setup, include=FALSE}
# In the YAML above, spaces matter!
library(flexdashboard)
library(tidyverse)
library(palmerpenguins)
library(fontawesome) # free icons to use in RMD document
library(plotly) # interactive plots
library(DT) # "DataTable" for interactive tables
data("penguins") # start typing penguins on next line to get the  to convert to dataframes
```



Plots {data-navmenu="Pages"}  
=======================================================================



Sidebar {.sidebar}
-----------------------------------------------------------------------

### Penguin Stats

The number of penguins in the data is `r nrow(penguins)`.

Row
-----------------------------------------------------------------------

### Number of penguins

```{r}
valueBox(nrow(penguins), icon = "fa-linux") # from font awesom
# see fontawesome.com for tons of fonts and icons
```




### Avg body mass

```{r}
avg_mass = round(mean(penguins$body_mass_g, na.rm = T), 1)

gauge(avg_mass,
      min(0),
      max(penguins$body_mass_g, na.rm = T),
      gaugeSectors(success = c(4000, 6300),
                   warning = c(2000, 3999),
                   danger = c(0, 1999)))
```

Column {.tabset}
-----------------------------------------------------------------------

### Scatterplot of bill length vs bill depth

```{r}
a <- penguins %>% ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) +
  geom_point()# after "x =" hit tab for variables to show up
ggplotly(a)
# htmlwidgets.org has all kinds of amazing plots to use in dashboards
```

Column {data-width=350}

### Chart B

```{r}
penguins %>% ggplot(aes(x = body_mass_g, y = sex, fill = sex))+
  geom_boxplot()
```

### Chart C

```{r}
penguins %>% ggplot(aes(x = flipper_length_mm, fill = species))+
  geom_histogram(bins=30) +
  facet_wrap(~species)
```

Data {data-navmenu="Pages"}
==============================================================================

```{r}
penguins %>% datatable(extensions = "Buttons",
                       options = list(dom = "Blfrtip",
                                      buttons = c("copy", "csv", "excel", "pdf", "print")))  # datatable from DT package  
# l = length
# p = pagination (ability to go from page 1 to page 2)
# B = add buttons
# default is lfrtip
# datatables.net has all the options to customize your html table
```